DeepInfer: High-performance inference framework for DeepSeek models(github.com)
2303 points by ggcr 5 days ago | 884 comments
tl;dr: DeepSeek has open-sourced DeepInfer, the inference framework powering its production services, built on vLLM with influences from SGLang and TensorRT-LLM. It supports DeepSeek-V4.1-Flash on NVIDIA SM100 GPUs and Huawei Ascend 950 NPUs, featuring optimized kernels (FlashMLA, DeepGEMM), speculative decoding with confidence-scheduled verification, batch-invariant and deterministic inference, async scheduling, and structured outputs. The release covers offline inference only—a KV cache system, prefill/decode disaggregation, and load balancing are required but not included for a full serving stack.
HN Discussion:
  • ↑Impressed by DeepInfer's throughput and revenue metrics in production
  • •Release is a strategic/geopolitical move timed against US restrictions on DeepSeek
  • ↑Open-sourcing undermines US frontier labs' business models and valuations
  • ↑Supporting Huawei Ascend NPUs could challenge Nvidia's hardware dominance
  • ↓Skeptical of China/DeepSeek's motives for open-sourcing this framework